17 citations · 21 across the 9 of their papers we have counts for
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cs.LG2024★ 17 cited
Can We Enhance the Quality of Mobile Crowdsensing Data Without Ground Truth?
Jiajie Li, Bo Gu, Shimin Gong +2
Mobile crowdsensing (MCS) has emerged as a prominent trend across various domains. However, ensuring the quality of the sensing data submitted by mobile users (MUs) remains a compl…
cs.LG2023★ 1 cited
Federated Learning Robust to Byzantine Attacks: Achieving Zero Optimality Gap
Shiyuan Zuo, Rongfei Fan, Han Hu +2
In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks. At each user, model parameter is firstly…